Speech recognition systems, such as, ASR system (ASR: Automatic Speech Recognition) and the like provide electronic apparatuses with easy-to-use user interfaces. One of the problems a speech recognition system faces is a problem concerning how to distinguish target words that should be recognized (In Vocabulary (IV)) from sounds that are to be excluded as recognition targets (Out Of Vocabulary (OOV)), such as, “er . . . ,” “well . . . ,” coughing and the like.
As a prior art document in this field, U.S. Pat. No. 2,886,177 can be enumerated. The speech recognition system can use Hidden Markov Models for modeling sounds in a sequence of speech sounds. Each elemental speech sound is known as a phoneme, and can be modeled by an individual Hidden Markov Model. Recognition target words and sentences are defined as combinations of phonemes in a grammar file. The grammar file is a file that defines as to which one of phoneme (Hidden Markov Model) sequences composes each of recognition target words-sentences. Input speech sound can be recognized according to the probability of matching a feature vector sequence extracted from the input speech sound with a Hidden Markov Model sequence defined in the grammar file.
However, signals that do not exist in a grammar file or a dictionary (OOV sounds) may be inputted in the speech recognition system. These OOV sounds are judged to be OOV or IV through calculation of the probability of matching them with OOV sound models and the probability of matching them with IV word models.
Normally, Hidden Markov Models used for modeling those OOV sounds are called filler models. There is still a room for performance improvement in the performance of the most advanced filler models. In particular, it is difficult to minimize both “false positive (to recognize OOV as IV)” and “false negative (to recognize IV as OOV),” in other words, to realize a speech recognition apparatus that does not recognize words and sounds undesired to be recognized, and recognizes words that should be recognized, and attempts are being made to improve the performance thereof in this respect.